Sequencing of Polyclonal Antibodies by Integrating Intact Mass, Middle–Down, and De Novo Bottom–Up Mass Spectrometry

peer-reviewed · Molecular & Cellular Proteomics · 2025

peer-reviewed · Molecular & Cellular Proteomics · 2025. Lei Xin et al. Polyclonal antibodies (pAbs) represent nature’s approach to robust immunity, targeting multiple sites on…
Date 2025-11-01
Type peer-reviewed
Venue Molecular & Cellular Proteomics
Publisher Elsevier BV
Contribution downstream-application
DOI 10.1016/j.mcpro.2025.101088
Citations (OpenAlex) 2
Venue 2-year citedness 4.69

Abstract

Polyclonal antibodies (pAbs) represent nature’s approach to robust immunity, targeting multiple sites on pathogens, but their complex mixtures have remained largely unsequenceable, limiting their therapeutic potential. While monoclonal antibodies (mAbs) dominate therapeutics because of their reproducibility, pAbs offer superior resilience against viral mutations and broader target recognition. Current pAb sequencing attempts have shown limitations, requiring germline databases or B-cell sequencing. Due to the highly variable nature of antibodies, as well as the possibility of unavailable B cells, there is a need for a purely mass spectrometry- and de novo sequencing-based solution. Here, we present PolySeq.AI, an automated de novo workflow that combines bottom-up, middle-down, and intact mass analysis, to accurately sequence pAb samples without relying on external databases. PolySeq.AI achieved >99% sequencing accuracy across all tested samples, including an mAb mixture from the HB-95 cell line and a mixture of four mAbs, with complete bottom-up coverage and strong middle-down fragment support. Importantly, recombinant antibodies produced from our de novo sequences of HB-95 antibodies retained full binding capabilities to human leukocyte antigen-I complexes, confirming the accuracy and efficacy of our pAb de novo sequencing workflow.

Authors

  1. Lei Xin · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University
  2. Wenting Li · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., University of Waterloo
  3. Shuyang Zhang · Bioinformatics Solutions (Canada)
  4. Ngoc Hieu Tran · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., University of Waterloo
  5. Zheng Chen · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc.
  6. Jun Ma · Bioinformatics Solutions Inc.
  7. Chao Peng · Baizhen Biotechnologies Inc.
  8. Ailee Aihemaiti · Bioinformatics Solutions (Canada)
  9. Kyle Hoffman · Bioinformatics Solutions (Canada)
  10. Xiyue Zhang · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc.
  11. Weiping Sun · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University
  12. Linting Li · Bioinformatics Solutions (Canada)
  13. Zihao Wang · Bioinformatics Solutions (Canada)
  14. Ming Li · Bioinformatics Solutions Inc., Central China Institute of Artificial Intelligence, Peng Cheng Laboratory, University of Waterloo, University of Western Ontario
  15. Baozhen Shan · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University

Methods and tools

  • PolySeq.AI: An automated workflow that integrates de novo bottom-up, middle-down and intact mass spectrometry to sequence polyclonal antibody mixtures without germline databases or B-cell sequencing, validated by expressing recombinant antibodies.

Methods it uses

  • ALPS: Assembles de novo sequenced peptides and their per-residue confidence scores into a de Bruijn graph to reconstruct complete monoclonal antibody heavy and light chains without a template.

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